When analyzing sensitive data in a cloud-deployed Hadoop stack, data-in-transit security needs to be enabled, especially in the underlying storage tier. This, however, will affect the performance of the system and may partially offset the cost benefits of the cloud. In this paper, we discuss two strategies for securing HBase deployments in the cloud. For both, we present benchmarking results which show performance impacts that significantly exceed the suggested 10% from the official documentation. These results demonstrate (i) that security configurations should follow a rational decision process based on benchmarking results and (ii) that the security architecture of HBase/HDFS should be redesigned with an emphasis on performance.